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DBMS > Apache IoTDB vs. EsgynDB vs. GridGain vs. Kdb vs. TinkerGraph

System Properties Comparison Apache IoTDB vs. EsgynDB vs. GridGain vs. Kdb vs. TinkerGraph

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonGridGain  Xexclude from comparisonKdb  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGridGain is an in-memory computing platform, built on Apache IgniteHigh performance Time Series DBMSA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelTime Series DBMSRelational DBMSKey-value store
Relational DBMS
Time Series DBMS
Vector DBMS
Graph DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websiteiotdb.apache.orgwww.esgyn.cnwww.gridgain.comkx.comtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.gridgain.com/­docs/­index.htmlcode.kx.com
DeveloperApache Software FoundationEsgynGridGain Systems, Inc.Kx Systems, a division of First Derivatives plc
Initial release2018201520072000 infokdb was released 2000, kdb+ in 20032009
Current release1.1.0, April 2023GridGain 8.5.13.6, May 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infofree 32-bit versionOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaJava, C++, .NetqJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyesyesno
Secondary indexesyesyesyesyes infotable attribute 'grouped'no
SQL infoSupport of SQLSQL-like query languageyesANSI-99 for query and DML statements, subset of DDLSQL-like query language (q)no
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
TinkerPop 3
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Groovy
Java
Server-side scripts infoStored proceduresyesJava Stored Proceduresyes (compute grid and cache interceptors can be used instead)user defined functionsno
Triggersyesnoyes (cache interceptors and events)yes infowith viewsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardinghorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication between multi datacentersyes (replicated cache)Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyes (compute grid and hadoop accelerator)no infosimilar paradigm used for internal processingno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistencynone
Foreign keys infoReferential integritynoyesnoyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyesyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsrights management via user accountsno
More information provided by the system vendor
Apache IoTDBEsgynDBGridGainKdbTinkerGraph
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
Apache IoTDBEsgynDBGridGainKdbTinkerGraph
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